Summarizing an Ontology: A "Big Knowledge" Coverage Approach

Ling Zheng, Yehoshua Perl, Gai Elhanan, Christopher Ochs, James Geller, Michael Halper

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Maintenance and use of a large ontology, consisting of thousands of knowledge assertions, are hampered by its scope and complexity. It is important to provide tools for summarization of ontology content in order to facilitate user "big picture" comprehension. We present a parameterized methodology for the semi-automatic summarization of major topics in an ontology, based on a compact summary of the ontology, called an "aggregate partial-area taxonomy", followed by manual enhancement. An experiment is presented to test the effectiveness of such summarization measured by coverage of a given list of major topics of the corresponding application domain. SNOMED CT's Specimen hierarchy is the test-bed. A domain-expert provided a list of topics that serves as a gold standard. The enhanced results show that the aggregate taxonomy covers most of the domain's main topics.

Original languageEnglish (US)
Title of host publicationMEDINFO 2017
Subtitle of host publicationPrecision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics
EditorsZhao Dongsheng, Adi V. Gundlapalli, Jaulent Marie-Christine
PublisherIOS Press
Pages978-982
Number of pages5
ISBN (Electronic)9781614998297
DOIs
StatePublished - Jan 1 2017
Event16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 - Hangzhou, China
Duration: Aug 21 2017Aug 25 2017

Publication series

NameStudies in Health Technology and Informatics
Volume245

Other

Other16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017
CountryChina
CityHangzhou
Period8/21/178/25/17

All Science Journal Classification (ASJC) codes

  • Health Information Management
  • Health Informatics
  • Biomedical Engineering

Keywords

  • Big knowledge
  • Ontology summarization
  • Topic coverage

Cite this

Zheng, L., Perl, Y., Elhanan, G., Ochs, C., Geller, J., & Halper, M. (2017). Summarizing an Ontology: A "Big Knowledge" Coverage Approach. In Z. Dongsheng, A. V. Gundlapalli, & J. Marie-Christine (Eds.), MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics (pp. 978-982). (Studies in Health Technology and Informatics; Vol. 245). IOS Press. https://doi.org/10.3233/978-1-61499-830-3-978